Self-harm, somatic disorders and mortality in the 3 years following a hospitalisation in psychiatry in adolescents and young adults
Bibliographic record
Abstract
BACKGROUND: There is limited recent information regarding the risk of self-harm, somatic disorders and premature mortality following discharge from psychiatric hospital in young people. OBJECTIVE: To measure these risks in young people discharged from a psychiatric hospital as compared with both non-affected controls and non-hospitalised affected controls. METHODS: Data were extracted from the French national health records. Cases were compared with two control groups. CASES: all individuals aged 12-24 years, hospitalised in psychiatry in France in 2013-2014. Non-affected controls: matched for age and sex with cases, not hospitalised in psychiatry and no identification of a mental disorder in 2008-2014. Affected controls: unmatched youths identified with a mental disorder between 2008 and 2014, never hospitalised in psychiatry. Follow-up of 3 years. Logistic regression analyses were conducted with these confounding variables: age, sex, past hospitalisation for self-harm, past somatic disorder diagnosis. FINDINGS: The studied population comprised 73 300 hospitalised patients (53.6% males), 219 900 non-affected controls and 9 683 affected controls. All rates and adjusted risks were increased in hospitalised patients versus both non-affected and affected controls regarding a subsequent hospitalisation for self-harm (HR=105.5, 95% CIs (89.5 to 124.4) and HR=1.5, 95% CI (1.4 to 1.6)), a somatic disorder diagnosis (HR=4.1, 95% CI (3.9-4.1) and HR=1.4, 95% CI (1.3-1.5)), all-cause mortality (HR=13.3, 95% CI (10.6-16.7) and HR=2.2, 95% CI (1.5-3.0)) and suicide (HR=9.2, 95% CI (4.3-19.8) and HR=1.7, 95% CI (1.0-2.9)). CONCLUSIONS: The first 3 years following psychiatric hospital admission of young people is a period of high risk for self-harm, somatic disorders and premature mortality. CLINICAL IMPLICATIONS: Attention to these negative outcomes urgently needs to be incorporated in aftercare policies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".